Cell image augmentation for classification task using GANs on Pap smear dataset

• Autorzy: Zak Jakub , Grzeszczyk Michal K. , Pater Antonina , Roszkowiak Lukasz , Siemion Krzysztof , Korzynska Anna

Identyfikatory

DOI

10.1016/j.bbe.2022.07.003

• Języki publikacji: EN

Abstrakty

EN

One of the solutions to the problem of insufficiently large training datasets in image processing is data augmentation. This process artificially extends the size of training datasets to avoid overfitting. Generative Adversarial Networks yield that become increasingly difficult to differentiate from real images, until the differentiation is no longer possible. Thus, artificial images closely resembling original ones can be generated. Inclusion of artificial images contributes to improving the training process. Medical domain is one of the areas where data acquisition is burdened by many procedures, laws, and prohibitions. As a result the potential size of collected datasets is reduced. This article presents the results of training Convolutional Neural Networks on a artificially extended image datasets. The resulting classification accuracy on a cell classification task of models trained with images generated using the proposed method were increased by up to 12.9% in comparison to that of the model trained only with original dataset from the HErlev Pap smear dataset.

Słowa kluczowe

EN

data augmentation; cell image; GAN image generation

PL

rozszerzanie danych; obraz komórki; generowanie obrazu; GAN

• Wydawca: Nałęcz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences ; Elsevier
• Czasopismo: Biocybernetics and Biomedical Engineering
• Rocznik: 2022
• Tom: Vol. 42, no. 3
• Strony: 995--1011
• Opis fizyczny: Bibliogr. 83 poz., rys., tab.

Twórcy

autor

Zak Jakub

• Laboratory of Processing Systems of Microscopic Image Information, Nalecz Institute of Biocybernetics and Biomedical Engineering Polish Academy of Sciences, Ks. Trojdena 4, 02-109 Warsaw, Poland

autor

Grzeszczyk Michal K.

• Faculty of Electronics and Information Technology, Warsaw University of Technology, Warsaw, Poland
• Sano Centre for Computational Medicine, Cracow, Poland

autor

Pater Antonina

• Laboratory of Processing Systems of Microscopic Image Information, Nalecz Institute of Biocybernetics and Biomedical Engineering Polish Academy of Sciences, Warsaw, Poland

autor

Roszkowiak Lukasz

• Laboratory of Processing Systems of Microscopic Image Information, Nalecz Institute of Biocybernetics and Biomedical Engineering Polish Academy of Sciences, Warsaw, Poland

autor

Siemion Krzysztof

• Laboratory of Processing Systems of Microscopic Image Information, Nalecz Institute of Biocybernetics and Biomedical Engineering Polish Academy of Sciences, Warsaw, Poland

autor

Korzynska Anna

• Laboratory of Processing Systems of Microscopic Image Information, Nalecz Institute of Biocybernetics and Biomedical Engineering Polish Academy of Sciences, Warsaw, Poland

Bibliografia

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